Instrument Manufacturers Research Articles

Mechanisms of Organizational Imprinting: From Entrepreneur to Organization

Entrepreneurs can have a long-lasting impact on organizations they found, despite significant changes in the environment. Imprinting theory offers an explanation for this. Yet, knowledge of how imprinting occurs is still limited. Scholars have therefore called for more attention to processes and micro-level theories of imprinting, including the role of individuals. I therefore ask, how do entrepreneurs imprint organizations? Drawing on material from company archives, I conducted a longitudinal, historical case study of Zeiss, a German manufacturer of optical instruments, covering the period 1846–1990. I show how individual blueprints of the founder and his business partner were translated into persistent features of the organization through early decisions, teaching, role modeling, and formalized rules, which left structural, behavioral, and product imprints. The article extends theory on imprinting by shedding light on blueprints as sources of imprints, the multiple mechanisms by which individuals persistently shape core features of an organization, and the multiple organizational dimensions on which imprints are left.

SurfILE: An Open-Source Python Package for Surface Topography Analysis

Surface metrology deals with inspecting surfaces and profiles by using contact or non-contact profilometers. In this field, the characterization of the dimensional, morphological, and texture parameters of samples as well as the assessment of metrological characteristics of measuring instruments are key issues. Manufacturers of instruments provide commercial software tools to analyze topography data. There are also freely available tools, including open-source options, that provide a variety of algorithms and methods. The rapid growth of investigations aimed at better understanding the effects of the microscale phenomena requires the improved traceable calibration of samples, the development of new methodologies and measuring techniques, and the specification of new mathematical models and processing techniques. In this work, we present SurfILE, the launch of an open-source Python project that provides various procedures and algorithms for topography analysis. The open-source software presented in this article is intended to be modular, expandable, and customizable.

Reducing manual targeted LC-MS/MS peak integration using a supervised learning peak evaluation and automated review tool

BackgroundOur laboratory analyses over 100,000 samples for multiple analytes yearly. Correctly annotating and quantifying analytes using targeted MS/MS analysis is crucial for most laboratories. Therefore, mass spectrometric instrument manufacturers include software capable of automatic chromatographic peak detection and integration, which is used for most routine applications. Although this generally works well, mistakes such as accidentally selecting a nearby matrix peak or drawing an incorrect baseline are relatively common. Especially when results are to be used for enforcement, a time-consuming manual review of each integrated peak is still required to obtain reliable results. This work aims to provide a tool that can significantly reduce the manual workload of reviewing peak integration, thereby reducing the time used for manual review while ensuring that errors made by automatic integration can be corrected by human experts. ResultsPeak Evaluation and Automated Review tool, or PEAR review, is a machine learning-type tool that can read automatic integrations from various brands of MS equipment and compare them with a set of examples stored in a database of correct peak integrations provided by analysts that are relevant for the type of analysis. Moreover, the automatic review process checks all available ion transitions for a target compound. With those ingredients, the tool can autonomously decide how a peak should be quantified or whether a human expert should review it. The developed tool was tested on routine data processed with a widely used vendor-specific software, and we found that 85% of all chromatograms were handled automatically by this tool. Only the remaining 15% needed a ‘conventional’ manual review. The qualitative and quantitative performance of the PEAR tool was found to be equivalent to that of expert human integration, underlining its reliability. SignificanceOur findings indicate that 85% of all manual integration checks can be skipped using PEAR. This reduces the often tedious workload of reviewing all peaks in multiple chromatograms while offering the same quality as full human intervention.

Direct method for microscale manipulation at liquid-liquid interfaces in ionic liquid media with real-time electron microscopy observation

A deep understanding of the processes in soft matter systems with liquid-liquid phase boundaries is of particular importance for materials science, chemistry and life sciences. A vast variety of physicochemical techniques have been proposed for the study of interfacial properties of liquid systems. Among them, electron microscopy methods occupy an important place due to the possibility of direct observation of the sample areas of interest with high spatial resolution; however, the harsh conditions of the electron microscope chamber impose significant restrictions on the possibilities of observing and manipulating unprotected liquids and related soft systems. To overcome these difficulties, in this work, we developed a methodology for direct probing of liquid-liquid interfaces with simultaneous control of the process using electron microscopy. Practically relevant liquid mixtures based on vacuum-compatible ionic liquid (IL) with water additives were probed with micrometer accuracy in real time inside an electron microscope chamber, which made it possible to reveal the role of specific ions aggregation and electrostatic phenomena in the stabilization of liquid microdomains. To test the versatility of the proposed approach, the morphology of a typical IL/water mixture was examined using a series of electron microscopes of various configurations, and it was shown that the best level of contrast between two chemically related liquid phases can be obtained in the case of a cold field emission electron source in combination with an in-lens secondary electron detector, regardless of the specific instrument manufacturer.

Memory high temperature production logging technology and applications

Abstract As oil exploration and development gradually move towards exploring deep oil and gas reservoirs, the formation temperature and pressure have significantly increased. Taking the Bohai buried hill oil and gas reservoir as an example, the formation temperature is generally above 180 °C, and conventional testing instruments cannot work stably under such high temperature conditions. Related instrument and equipment manufacturers optimize and innovate logging instruments in multiple directions such as welding, modularization, and material selection. To solve the temperature resistance problem of instruments, thermal insulation coatings, vacuum flask, and other methods are commonly used for temperature isolation. This article mainly introduces a high-temperature production logging Vulcan™ developed by SDI Company. The FLS 1.44 series instrument has the characteristics of small outside diameter(OD) and high temperature resistance, and adopts a memory measurement method to avoid short circuit and operating costs of high-temperature cables. Through on-site operation in Well A, multiple consecutive production profile tests were conducted in a high-temperature environment with a formation temperature of about 185 °C. The sensors sensor exhibits good characteristics in stability, and the response of each parameter measurement curve was good under different passes. The testing task was successfully completed, and the application effect of the testing instrument was good.

Assessment of wood quality for Sape making: Vibroacoustic analysis and machine learning classification

Sape is a popular traditional musical instrument from Sarawak, Malaysia. This instrument is handmade and differs in wood, dimension, design, etc. This impedes the preservation and promotion of the Sape tradition, as well as the development of new Sape instruments. Wood is the primary factor affecting Sape sound, and this study aimed to evaluate the quality of three commonly used types of wood in the instrument manufacturing. Rectangular wood samples were fashioned and tested for physical, vibroacoustic, and timbre characteristics using a flexural vibration test. The objective was to identify the top features influencing the sound quality and develop a reliable method for classifying wood quality. Results showed that Adau wood had the highest quality, followed by Merbau and Tapang wood. Four key features, including acoustic radiation damping coefficient, spectral flux, spectral centroid, and inharmonicity, were selected by the MRMR algorithm and used to train and test various classifiers in MATLAB. The decision tree classifier achieved 98.1% accuracy in predicting wood quality. This study demonstrates the potential of using machine learning to classify Sape wood quality and provides a useful guide for its production. The findings could contribute to the preservation and advancement of this cultural tradition.

B-113 Beckman Coulter DxI 9000 immunoassay analyzer assay performance meets new CLIA 2024 performance goals with highest proportion of Six Sigma performance amongst all major manufacturers

Abstract Background The Clinical Laboratory Improvement Act (CLIA) proficiency testing (PT) criteria will be updated in July 2024 with some goals tightening by up to 40%. It is assumed, but not known, that all assays and instruments will be able to achieve these goals. Using these new CLIA 2024 goals, estimates of current instrument group performance from an international proficiency testing (PT) survey have shown significant differences in quality, calling into question which assays can achieve the new CLIA goals. Currently, the highest performing diagnostic instrument achieves only 35.2% 6-Sigma, while the majority of instruments have less than 15% 6-Sigma performance indicating a higher probability of future PT failures. Methods Eighteen assays that will be governed by new CLIA 2024 goals were assessed for Sigma metric performance on the DxI 9000 immunoassay analyzer: Alpha Fetoprotein (AFP), Beta hCG, Carcinoembryonic antigen (CEA), Cortisol, Creatine Kinase MB (CK-MB), Estradiol, Ferritin, Folate, Follicle-Stimulating Hormone (FSH), Prolactin, Para-thyroid hormone (PTH), Total Prostate specific antigen (Total PSA), Testosterone, Thyroid Stimulating Hormone (TSH), Total Triiodothyronine (TT3),high sensitivity Troponin I, Total Thyroxine (TT4) and Vitamin B12. Precision and bias were determined following CLSI EP5 and EP9 guidelines, measured across 3 reagent lots. CLIA 2024 PT criteria provides the allowable total error for the standard Sigma-metric calculation: Sigma-metric = (TEa - |bias|) / SD Performance of the other major analyzers was assessed using the methodology introduced in 2006 by Westgard JO and Westgard SA. The Sigma-metric predicts future problems with PT and potential optimization of QC procedure opportunities, including fewer Westgard Rules, control levels, even reduced QC frequency and materials leading to less cost and time saved. Results Half (50%) of the assays on DxI 9000 achieves 6-Sigma, outperforming all other major manufacturers in the market who range from only 5% to 35% 6-Sigma. Further, over 78% of the DxI 9000 performance was 4Sigma and higher. Less than 8% of performance fell below 3-Sigma, which was observed at the extreme ends of the reportable range. Conclusions The DxI 9000 assay performance is well designed to meet CLIA 2024’s new PT criteria and has the highest prevalence of 6-sigma assay performance observed on market when compared to the top 5 major instrument manufacturers. Assays with Sigma metrics at 4-Sigma and higher are unlikely to face analytical PT difficulties and can be optimized for reduced Westgard Rules, control levels, and potentially even QC frequency.

Electrification of a Mini Traction Machine and Initial Test Results

Electric vehicles (EVs) continue to evolve, and sales continue to increase as the world pushes toward improved sustainability. This drives the need for research to understand the unique environments in which fluids operate within the Electric Drive Units (EDUs) of EVs in order to improve durability and reduce frictional losses. However, for this to happen, test rigs are required to operate with an electric current passing across the test parts and through the lubricant. Very few electrified test rigs currently exist, with most being adaptations of rigs undertaken by academia and independent and national research labs. In this work, the PCS Mini Traction Machine (MTM) was modified to supply a voltage across a tribological contact. New parts for the MTM were designed in collaboration with the instrument manufacturer. Work was undertaken in both the author’s labs and the manufacturer’s labs with the aim of bringing a commercially available unit to market as quickly as possible. A test matrix was completed on the MTM utilizing a range of temperatures, loads, and voltage inputs for three different lubricants commonly used in EDUs. The test matrix consisted of 36 test conditions, with some runs performed in triplicate, resulting in 81 tests for each oil and a total matrix of 243 tests. The test matrix was run to obtain the results and to test the robustness of the rig design. After testing was completed, the MTM disc wear scars were measured. The results from these measurements indicate that the application of alternating current (AC) and direct current (DC) causes a significant increase in the wear scar compared to non-electrified test conditions. This, in turn, results in increased traction values under non-electrified conditions. It was also noted that the repeatability of the traction curves and end-of-test wear was reduced under both AC and DC electrified conditions.

Application of ferromagnetic materials for technological processes thermal regime stabilization (Review)

The research focuses on the technological and auxiliary equipment used in various industries that require maintaining a specific narrow temperature range. The study aims to critically analyze the potential use of structural elements made of ferromagnetic materials with a second-kind phase transition temperature (Curie temperature or Curie point) in high-performance, knowledge-intensive industries, particularly the chemical industry. These materials correspond to the required temperature of the processed or transported liquid or loose medium. The technological processes using the magnetothermal effect and the corresponding designs of equipment are considered: heat exchange, heat and mass exchange, mechanical and hydromechanical, equipment for processing thermoplastics, as well as other devices used in various branches of industry, in particular chemical, food and microbiological, in thermal energy, metallurgy, agriculture, medicine and construction. It is shown that the specified method of ensuring the required thermal regime is suitable for use primarily in large-tonnage continuous production. As the conducted studies have shown, the proposed approach to stabilizing the heat flow of various technological and auxiliary equipment is effective and quite promising. The indisputable advantage of the corresponding method is to ensure a certain temperature of the working parts of the equipment with high accuracy, however, this method is quite difficult to implement on the existing equipment, which is mostly made of magnetic materials (steel, cast iron). Therefore, to implement the proposed method in practice, it is necessary to develop new equipment designs or to subject existing samples to deep modernization. At the same time, there may be difficulties associated with the search for existing or the creation of new ferromagnetic materials with the required thermomagnetic properties for the manufacture of appropriate structural elements of technological and auxiliary equipment. However, in certain cases, the proposed method of maintaining the specified temperature of the processed media may become the most appropriate (primarily in fine chemical technology, biotechnology, pharmaceuticals, precision instrument manufacturing, microelectronics, and medicine).

Interrogating data-independent acquisition LC–MS/MS for affinity proteomics

AbstractData-Independent Acquisition (DIA) LC–MS/MS is an attractive partner for co-immunoprecipitation (co-IP) and affinity proteomics in general. Reducing the variability of quantitation by DIA could increase the statistical contrast for detecting specific interactors versus what has been achieved in Data-Dependent Acquisition (DDA). By interrogating affinity proteomes featuring both DDA and DIA experiments, we sought to evaluate the spectral libraries, the missingness of protein quantity tables, and the CV of protein quantities in six studies representing three different instrument manufacturers. We examined four contemporary bioinformatics workflows for DIA: FragPipe, DIA-NN, Spectronaut, and MaxQuant. We determined that (1) identifying spectral libraries directly from DIA experiments works well enough that separate DDA experiments do not produce larger spectral libraries when given equivalent instrument time; (2) experiments involving mock pull-downs or IgG controls may feature such indistinct signals that contemporary software will struggle to quantify them; (3) measured CV values were well controlled by Spectronaut and DIA-NN (and FragPipe, which implements DIA-NN for the quantitation step); and (4) when FragPipe builds spectral libraries and quantifies proteins from DIA experiments rather than performing both operations in DDA experiments, the DIA route results in a larger number of proteins quantified without missing values as well as lower CV for measured protein quantities.

NinjaCap: a fully customizable and 3D printable headgear for functional near-infrared spectroscopy and electroencephalography brain imaging.

Accurate sensor placement is vital for non-invasive brain imaging, particularly for functional near-infrared spectroscopy (fNIRS) and diffuse optical tomography (DOT), which lack standardized layouts such as those in electroencephalography (EEG). Custom, manually prepared probe layouts on textile caps are often imprecise and labor intensive. We introduce a method for creating personalized, 3D-printed headgear, enabling the accurate translation of 3D brain coordinates to 2D printable panels for custom fNIRS and EEG sensor layouts while reducing costs and manual labor. Our approach uses atlas-based or subject-specific head models and a spring-relaxation algorithm for flattening 3D coordinates onto 2D panels, using 10-5 EEG coordinates for reference. This process ensures geometrical fidelity, crucial for accurate probe placement. Probe geometries and holder types are customizable and printed directly on the cap, making the approach agnostic to instrument manufacturers and probe types. Our ninjaCap method offers probe placement accuracy. Over the last five years, we have developed and validated this approach with over 50 cap models and 500 participants. A cloud-based ninjaCap generation pipeline along with detailed instructions is now available at openfnirs.org. The ninjaCap marks a significant advancement in creating individualized neuroimaging caps, reducing costs and labor while improving probe placement accuracy, thereby reducing variability in research.

Glide Path in Endodontics: A Literature Review of Current Knowledge.

The introduction of nickel-titanium rotary instruments revolutionized shaping procedures as they were able to produce a well-tapered preparation while reducing operator fatigue. The major drawback of rotary instruments was the high risk of fracture due to bending and torsional stress. Thus, the creation of a glide path has been advocated and recommended by most rotary instrument manufacturers. The aim of the present review is to summarize existing knowledge on glide path preparation and identify areas where further research is needed. The primary goal is to provide a comprehensive overview of the techniques and instruments used in glide path preparation, highlighting their advantages and limitations. The secondary goal is to explore the effect of glide path creation on the overall success of endodontic treatment, particularly in terms of reducing procedural errors and improving treatment outcomes. An online search on PubMed, ScienceDirect, UCLA, and Scopus databases was conducted, and 116 articles were identified. Eligible articles were divided into nine categories based on what they researched and compared. The categories included centering ability and/or root canal transportation, cyclic fatigue resistance, glide path and shaping time, tortional stress resistance, apical extrusion of debris and/or bacteria, defects in dentine walls, file separation, postoperative pain assessment, and scouting ability and performance. Establishing a glide path reduces root canal transportation, especially with rotary methods. Reciprocating and heat-treated files offer higher fatigue resistance and shorter preparation time. Instruments with shorter pitch lengths have greater torsional strength. Preparation and coronal preflaring reduce apical debris and bacteria. Glide paths do not affect dentine microcracks, file separation, or defects but reduce immediate postoperative pain and improve cutting ability. Randomized trials are needed to assess their impact on treatment outcomes.

TinyML-Raman: A novel IoT based field-deployable spectra analysis for accurate identification of pharmaceuticals and trace dye-pesticide mixtures from facile SERS method

BackgroundUpcoming inexpensive, compact Internet of Things (IoT) microcontrollers i.e., tiny-machine learning (TinyML) takes the ML driven Raman spectroscopy one step ahead for realization of more affordable and highly compact field deployable instruments. Further, lack of large spectral datasets and need for numerous specialized SERS substrates impede the development of various ML-based surface enhanced Raman spectroscopy (SERS) applications. The aim is to introduce TinyML analysis on wide range of spectra classes using customized dataset obtained with low-cost SERS. In this regard, it is vital to establish an optimum ML model and efficient data handling methodology for low memory TinyML units. ResultsWe introduce a novel TinyML methodology for accurate classification of large spectra classes with smartphone assistance for data communication and results visualization. To generate large customized spectral dataset, we present a facile, micro-drop SERS using Au colloids and reusable grooved Al substrates. The results demonstrated that memory efficient 8-bit data quantization based convolutional neural network is effective for accurate identification of 22 different spectra classes of trace dye-pesticide mixtures and pharmaceuticals. In this novel quantized data analysis on significantly varied intensity and complex variation spectra classes i.e., many individual, binary-mixtures and some with varied compositions, data normalization is shown to be powerful for improving ML classification accuracy from about 55 % to >99.5 %. Its robustness is demonstrated using inter-instrument driven data variations such as spectral shifts, high noise, and abscissa-flip, with five-fold cross validation of model performance. In addition, on-site quantification of analyte through spectral intensity is also demonstrated. SignificanceThis study opens up a new approach of ML analysis towards realization of next generation field deployable analytical instruments maintaining data privacy. It presents a detailed procedure of quantized spectral data analysis and its implementation in TinyML, attractive for various users and instrument manufacturers. The presented innovative computer-free ML analysis can be employed in all types of spectrometers, meeting the common goal of Raman spectroscopy i.e., accurate identification of complex spectra classes.

Enhancing precision through AI-enhanced method verification validating iron determination on the Alinity ci® Analyzer: Experience of the central laboratory of Mohammed VI University Hospital of Oujda

This study meticulously assessed the analytical performance of iron determination on the Alinity ci® analyzer, employing advanced AI-powered method verification techniques. Conducted at Mohammed VI University Hospital's central laboratory in Oujda, Morocco, the validation process strictly adhered to the rigorous guidelines outlined in the French accreditation committee's (COFRAC) Accreditation Technical Guide (GTA) 04. Through comprehensive assessments of repeatability and reproducibility, we definitively confirmed the assay's precision and reliability. Our evaluation yielded highly satisfactory results, consistently exceeding the established criteria set forth by both the instrument manufacturer and esteemed professional organizations like SFBC and RICOS. This unequivocally validates the laboratory's capability to deliver accurate and reproducible iron concentration measurements, crucial for enhanced clinical diagnostics and, ultimately, well-informed patient care decisions. This study underscores the importance of stringent validation processes in ensuring the reliability of diagnostic assays, thereby bolstering confidence in laboratory medicine practices and patient outcomes.

Discovering Ethnomathematics in Sundanese Gamelan: Explore Mathematics Aspect in Gamelan

Ethnomathematics is important in recent decades, specifically in the production of gamelan instruments. Therefore, this research aimed to examine the intricate relationship between mathematics and cultural craftsmanship in Sundanese gamelan instruments made at Gong Factory in Bogor, West Java. Ethnographic methods were used to observe and describe the practices of gamelan craftsmen and the data collection process comprised carefully selected artists. These individuals actively acquire data by reviewing relevant material, observing, analyzing, and interviewing. Miles and Huberman's framework for data analysis included data reduction, presentation, inference, and verification. The procedures understood the delicate relationship between mathematics and culture in the investigated setting. The results showed that Gong Factory in Bogor preserved and promoted a unique musical heritage. Furthermore, the instruments were known for exceptional sound quality, serving as cultural relics and didactic tools, as well as teaching visitors about the manufacturing process. The factory preserved culture through the manufacture of gamelan instruments including gong, bonang, and saron. In this context, the craftsmanship used mathematical principles, specifically precise proportions and ratios. The instruments' visual and auditory qualities depended on geometry. The results significantly impacted mathematics education by enhancing cross-cultural connections, improving proportional reasoning and mathematical comprehension, and recognizing the wider relevance of principles. Culture, mathematics, and education were connected, showing that conserving Indonesian musical tradition benefited local and global populations.

Intercomparison to validate implementations of different laboratories of algorithms for the analysis of surface texture

The surface texture is an important feature of machine parts for any kind of contact. The quantification of its properties has been a well-established area in quality assurance for many decades. With the increasing demand for precision and interchangeability in the globalised marketplace, the results of surface analysis must be unambiguous and reliable. This is why the International Standardization’s Technical Committee on Geometric Product Specification has updated its standards. Consequently, instrument manufacturers and calibration laboratories need to ensure that their analysis software complies with the new ISO standards. An intercomparison has therefore been carried out to validate surface texture analysis software. Over the past two decades, a number of tests have been conducted on surface texture measurement and analysis methods, including issues of instrument response, discretisation and quantisation. This article examines the numerical and computational aspects of analysis algorithms that process data sets of discrete values of finite floating-point precision as input. The method of testing texture analysis algorithms utilising software measurement standards (softgauges) and the specification of the test tasks are explained. The results of the comparison are presented and discussed.

Advancement in graphical user interface tailored quality classification of sape soundboard

This research introduces an innovative methodology for evaluating and predicting soundboard quality in the intricate craftsmanship of sape instruments. Despite the sape’s profound cultural significance, the process of selecting soundboard wood has been inadequately explored, resulting in uncertainties within the crafting community. Addressing this research gap, this study integrates advanced machine learning techniques and devises a specialized Graphical User Interface (GUI) tailored for sape makers. The methodology encompasses a thorough acoustic analysis of three distinct hardwoods—adau, merbau, and tapang—employing machine learning classification through Support Vector Machine with a Gaussian kernel. The study culminates in the development of a user-friendly GUI for soundboard quality assessment. Results underscore the model’s proficiency for achieving an optimized accuracy of 87.8% in classifying sape audio samples. The MATLAB App Designer-based GUI streamlines the evaluation process, offering a practical and accessible tool for craftsmen. This integrated approach, harmonizing traditional craftsmanship with cutting-edge technology, holds the potential to revolutionize sape instrument manufacturing, ensuring the preservation and progressive evolution of this rich cultural heritage.

Compensating Image Distortions in a Commercial Reflectron-Type Atom Probe.

In atom probe tomography, the spatial resolution and accuracy of the data critically depend on the 3D reconstruction of the 2D detector data. Atom probes with a reflectron have an improved mass resolving power and must include a model of the imaging properties of the reflectron. However, for modern wide-angle reflectron instruments, these imaging properties are not trivial and need to be determined for the reflectron used. This is typically done by the instrument manufacturer, and due to the proprietary nature of the instrument design, the imaging properties are opaque to the user. In this paper, we provide a method to determine the imaging properties of a reflectron that can easily be carried out on commercial instrumentation. This method is used to provide the user with a transformation function from the provided detector data, which can already contain some corrections applied, to a virtual detector placed before the reflectron. From there on, 3D reconstructions can be carried out analogous to straight flight path instruments. Correction algorithms and reference data for Imago/CAMECA LEAP 3000, 4000, 5000, and 6000 series instruments are also provided.

Characterization of Electrospray Ionization Complexity in Untargeted Metabolomic Studies.

The annotation of metabolites detected in LC-MS-based untargeted metabolomics studies routinely applies accurate m/z of the intact metabolite (MS1) as well as chromatographic retention time and MS/MS data. Electrospray ionization and transfer of ions through the mass spectrometer can result in the generation of multiple "features" derived from the same metabolite with different m/z values but the same retention time. The complexity of the different charged and neutral adducts, in-source fragments, and charge states has not been previously and deeply characterized. In this paper, we report the first large-scale characterization using publicly available data sets derived from different research groups, instrument manufacturers, LC assays, sample types, and ion modes. 271 m/z differences relating to different metabolite feature pairs were reported, and 209 were annotated. The results show a wide range of different features being observed with only a core 32 m/z differences reported in >50% of the data sets investigated. There were no patterns reporting specific m/z differences that were observed in relation to ion mode, instrument manufacturer, LC assay type, and mammalian sample type, although some m/z differences were related to study group (mammal, microbe, plant) and mobile phase composition. The results provide the metabolomics community with recommendations of adducts, in-source fragments, and charge states to apply in metabolite annotation workflows.

Multiscale assessment of artificial aging treatment of polysaccharides from tonewood species

In the acoustics of musical instruments with a resonator body, the aging of the wood leads to the improvement of the acoustic properties due to increasing the crystallinity of wood. This phenomenon could be explained by the fact that wood is a complex product based on three-dimensional polymer chains of carbohydrates, its aging being closely related to covalent cross-linking and scission of polymer chains. The aim of this study was to evaluate at a multiscale the changes produced artificial aging of tone wood by measuring the acoustic, mechanical and chemical parameters. The spruce and maple wood samples were investigated before and after exposure to ultraviolet (UV) radiation, through the tensile test, the time-of-flight method (TOF), the analysis of the wood color and the determination of the chemical fingerprint through Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). The obtained results showed that the effects of artificial aging are manifested at the chemical level where the crystallinity increases up to the acoustic level, depending on the wood species and their quality class. These results are relevant for musical instrument manufacturers to find treatments that lead to superior acoustic properties.